debugging

Guide root-cause investigation before applying fixes to bugs.

11|5|Updated Jan 9, 2026

Search Tags:#debugging #troubleshooting #software-development #phases #reproducibility #root-cause #systems-analysis

Ready to run

npx skills add https://github.com/rbergman/dark-matter-marketplace --skill debugging-rbergman

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/rbergman/dark-matter-marketplace/tree/main/plugins/workflow/skills/debugging
Command: npx skills add https://github.com/rbergman/dark-matter-marketplace --skill debugging-rbergman

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Random fixes waste time and create new bugs. This skill ensures root-cause investigation before any fix attempts, avoiding symptom fixes and wasted effort.

Core Features & Use Cases

Four-Phase methodology: Root cause investigation, pattern analysis, hypothesis testing, and implementation to resolve issues reliably.
Systematic data collection: Reproducing issues, gathering logs, and tracing data flow across components.
Use Case: When a bug appears in production, follow the four phases to identify root cause, verify with minimal changes, and implement a durable fix.

Quick Start

Follow Phase 1 to Phase 4: reproduce the issue, collect evidence, form hypotheses, test changes, and confirm resolution.

Frequently Asked Questions about debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is root-cause debugging and why is it necessary for software troubleshooting?▼

Root-cause debugging is a systematic troubleshooting method that identifies the fundamental cause of software failures before applying fixes. It prevents symptom patching and avoids wasted effort by enforcing structured evidence gathering, pattern analysis, and hypothesis testing.

How do I debug a production failure using a phased methodology?▼

To debug a production failure, follow a four-phase methodology: investigate the root cause by reproducing the issue and gathering logs, analyze patterns, test hypotheses with minimal changes, and implement a verified resolution. This ensures reliable issue resolution.

How do I stop applying random fixes that create new bugs during software development?▼

To stop applying random fixes that create new bugs, enforce root-cause investigation before any implementation. By systematically reproducing issues, tracing data flow, and testing hypotheses, you avoid symptom fixes and ensure durable solutions.

What is the best way to troubleshoot integration failures across system components?▼

The best way to troubleshoot integration failures is to perform systems analysis by tracing data flow across components. Gather logs, reproduce the issue, and verify fixes through structured hypothesis testing to resolve the failure reliably.

When should I use a structured debugging process instead of quick patches?▼

You should use a structured debugging process instead of quick patches whenever a bug appears in development, testing, production, or integrations. This approach enforces evidence gathering and progression criteria to prevent wasted effort and recurring issues.

Why does troubleshooting fail when I skip pattern analysis and hypothesis testing?▼

Troubleshooting fails when you skip pattern analysis and hypothesis testing because you lack the evidence needed to confirm the root cause. Implementing fixes without this structured progression risks creating new bugs and resolving only symptoms.